Best 35 Helpful ChatGPT Prompts for Coders (2023)

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As human coders, we need to adapt or die.

When Google released its powerful search capabilities a couple of decades ago, we needed to learn their search interface or become irrelevant. Because a coder capable of using search effectively is 10x more productive than one who doesn’t.

The same holds for large language models (LLMs), in particular, ChatGPT. Use it daily or become irrelevant.

And, no, I’m not affiliated with OpenAI or Google or any other big tech company.

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The key to leveraging the power of ChatGPT lies in using the right prompts to get most out of the model.

This article highlights 10 of the most effective prompts that can assist developers in honing their skills, tackling complex tasks, and becoming more productive — More with less!

The prompts cover various aspects of coding, such as optimization, learning new languages, and enhancing software design.

Getting Started with ChatGPT

As a powerful language model, ChatGPT can help you troubleshoot coding problems, refine your skills and generate new ideas. Let’s start with five essential prompts for coders to get started with ChatGPT. Easy peasy.

Prompt 1: Explain!

Explain how the {concept or function} works in {programming language}.

This prompt is useful when trying to understand a particular concept, function or language feature in depth. Example output:

Explain how the map function works in JavaScript.

ChatGPT will provide a brief explanation and an example of utilizing the map function within a JavaScript context.

Prompt 2: Syntax

What is the correct syntax for a {statement or function} in {programming language}?

This prompt allows you to quickly get the correct syntax for specific coding situations. Example output:

What is the correct syntax for a for loop in Python?

ChatGPT will provide a brief explanation along with a syntax example for a Python for loop.

Prompt 3: Bug Fixes

How do I fix the following {programming language} code? {code snippet}

This prompt is helpful when you encounter errors in your code and need assistance in debugging. Example output:

How do I fix the following JavaScript code? function greet() { console.log('Hello, world!' }

ChatGPT will identify the issue and suggest a correction, e.g., adding a missing parenthesis to the function definition.

Prompt 4: Best Practice

Show me best practices for writing {concept or function} in {programming language}.

Use this prompt to discover the best practices and recommended conventions for writing specific functions or incorporating concepts within a programming language. Example output:

Show me best practices for writing async/await functions in JavaScript.

ChatGPT will provide guidelines and recommendations for properly implementing async/await functions in JavaScript.

Prompt 5: Optimize!

Optimize the following {programming language} code: {code snippet}

This prompt effectively suggests how to make your code more efficient and optimized. Example output:

Optimize the following Python code: def square(numbers): result = [] for number in numbers: result.append(number * number) return result

ChatGPT may suggest using list comprehensions to achieve a more concise solution for the square function.

Debugging and Optimization

Ensuring optimal performance for your code is crucial. That is, if you avoid premature optimization — it is the root of all evil!

Debugging and optimization techniques help identify and resolve issues that could negatively affect functionality, efficiency, and user experience. Here are some of the most helpful ChatGPT prompts for debugging and optimization:

Prompt 6: “Find the bottleneck in this code block.”

codeBlock='''function example() {
  var startTime = new Date().getTime();
  // ... code ...
  var endTime = new Date().getTime();
  return (endTime - startTime) / 1000;
}'''

Identifying bottlenecks in your code is vital to enhance performance. This prompt will analyze the provided code block and locate any potential bottlenecks.

For example, ChatGPT may return:

"The bottleneck is in the 'code' section as it is taking the majority of the execution time."

This information helps you focus your optimization efforts on the problematic area.

Prompt 7: “Suggest ways to optimize this function.”

functionToOptimize='''function slowFunction(input) {
  // ... code...
}'''

This prompt aids in finding optimization opportunities within a specific function. ChatGPT might respond with:

"In the 'slowFunction' provided, you can optimize it by:
1. Using a more efficient algorithm for processing the input.
2. Implementing memoization to cache results.
3. Parallelizing the processing if applicable."

Prompt 8: “Detect memory leaks in this JavaScript code.”

codeWithMemoryLeaks='''function example() {
  var leaker = [];
  for (var i = 0; i < 1000; i++) {
    leaker.push(new Array(1000));
  }
}'''

Memory leaks can lead to degraded performance or application crashes. Identifying them is crucial for maintaining code health. With this prompt, ChatGPT could return:

"There is a potential memory leak in the 'example' function, as the 'leaker' array keeps growing and is never cleared or abandoned."

Knowing the location of the memory leak allows you to resolve the issue and prevent future negative consequences.

APIs and Integrations

This section is focused on APIs and Integrations, providing you with helpful ChatGPT prompts that can assist coders in managing API usage and implementation.

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These prompts will enable you to better understand and maintain APIs and integrate them into your projects seamlessly.

Prompt 9: API

Explain how to use the REST API for [service name].

Understanding how to use a specific REST API is crucial for integrating it into your projects. By specifying the service name in the prompt, ChatGPT will provide you with a detailed explanation of using the REST API, complete with authentication, endpoint structures, and relevant methods.

Example Output:

“To use the REST API for AcmeService, first, obtain an API key by signing up on their website. Then, use the following base URL for all your API requests: https://api.acmeservice.com/v1/. Authenticate each request by including the API key in the header…”

Prompt 10: Fetch Data

Write a Python function to fetch data from [API endpoint].

When working with APIs, it’s common to fetch data from various endpoints. This prompt will generate a Python function that retrieves data from the specified API endpoint, making it easier to interact with APIs through code.

Example Output:

def fetch_data_from_endpoint():
    import requests
    url = 'https://api.example.com/data'
    headers = {'Authorization': 'Bearer your_api_key'}
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        return response.json()
    else:
        return None

Prompt 11: List APIs

List five popular APIs in the category of [category].

Having a list of popular APIs in a specific category can help you choose the most suitable API for your project. With this prompt, ChatGPT will suggest five popular APIs that match your desired category.

Example Output:

"Five popular APIs in the category of payment processing include:
1. Stripe API
2. PayPal API
3. Square API
4. Braintree API
5. Authorize.Net API"

NLP and Machine Learning

For coders working in Natural Language Processing (NLP) and Machine Learning, ChatGPT can provide valuable insights and assistance.

Here are a few useful prompts that can help you get started:

Prompt 12: Tokenize

Explain how tokenization works in NLP and provide a Python example

This prompt helps coders understand the concept of tokenization in NLP and provides a practical Python example. An example output might be:

Tokenization is the process of breaking down a text into individual words or tokens. In Python, you can use the 'split()' function or libraries like NLTK or spaCy. Example: 

import nltk
text = "This is an example."
tokens = nltk.word_tokenize(text)
print(tokens)

Output: ['This', 'is', 'an', 'example', '.']

Prompt 13: Concepts I

Explain the difference between supervised and unsupervised machine learning

Understanding the distinction between supervised and unsupervised machine learning is crucial for coders. This prompt clarifies the differences with an example output:

Supervised learning uses labeled data to train a model that can make predictions, while unsupervised learning works with unlabeled data and aims to find patterns or relationships in the data. Examples of supervised learning include classification and regression, while clustering and dimensionality reduction are unsupervised learning methods.

Prompt 14: Concepts II

What are Overfitting and Underfitting in machine learning? How do they affect a model's performance?

This prompt covers essential topics like overfitting and underfitting, helping coders understand how they impact a model’s performance. An example output might be:

Overfitting occurs when a model learns the training data too well, including noise or random fluctuations, leading to poor generalization to new, unseen data. Underfitting occurs when a model fails to capture the underlying patterns in the training data, resulting in poor performance on training and new data. Both overfitting and underfitting can negatively affect a model's predictive accuracy and should be addressed by tuning hyperparameters or using techniques like cross-validation.

These prompts are beneficial for coders working in NLP and machine learning, providing essential knowledge, examples, and explanations of key concepts.

Advanced Features and Capabilities

ChatGPT is not just limited to answering questions; it can also provide code snippets, perform code reviews, and suggest optimizations.

Here are some useful prompts for coders to help them take advantage of ChatGPT’s advanced capabilities:

Prompt 15: Algorithm

Prompt: Generate a Python function to calculate the factorial of a number.

Reason: This prompt can help users quickly obtain a Python function to calculate factorials. It’s particularly helpful if you’re in the middle of development and don’t want to search online for a solution or write it yourself.

Example Output: def factorial(n): return 1 if n == 0 else n * factorial(n-1)

Explanation: This output provides a Python function that computes the factorial of a given number using recursion.

Prompt 16: Review Code

Prompt: Review this Python code for possible improvements: \ def slow_function(x): \ result = 0 \ for i in range(x): \ for j in range(x): \ result += i * j \ return result

Reason: Code reviews can be time-consuming, and sometimes you need a quick review of your code without waiting for a colleague. ChatGPT can help by providing suggestions for code optimization.

Example Output: Consider using list comprehensions for a more concise approach: \ def faster_function(x): \ return sum(i * j for i in range(x) for j in range(x))

Explanation: This output provides an alternative implementation of the given Python function, using list comprehensions and the built-in sum function for a more concise and efficient approach.

In addition to providing code snippets and code reviews, ChatGPT can also answer queries about various programming languages, frameworks, and tools, making it a versatile resource for developers.

Deployment and Scaling

Deployment and scaling are crucial aspects of a coder’s life. These ChatGPT prompts can guide you through deploying applications and managing their scalability efficiently.

Prompt 17: Steps to Deploy

Recommend steps to deploy a Python web application in a cloud environment.

This prompt helps provide assistance for deploying Python applications in the cloud.

Example output can include a list of steps that cover creating a virtual environment, packaging your code, and deploying to a cloud provider such as AWS or Google Cloud.

Prompt 18: Manage Apps

How do I manage scaling for a Node.js application on a server?

This prompt is useful when handling the scaling process for Node.js applications. Example output may include suggestions for using a reverse proxy, load balancing, and monitoring server resources like CPU and memory usage.

Prompt 19: Concepts III

Explain the concept of horizontal and vertical scaling, and when to use each.

With this prompt, you can better understand the differences between horizontal and vertical scaling, and the appropriate situations to apply them in.

Example output could involve an explanation of horizontal scaling (adding more servers) vs. vertical scaling (adding more resources to a single server), along with real-life scenarios that illustrate their use cases.

Custom Solutions and Applications

When working with ChatGPT for coding, one exciting aspect is creating custom solutions and applications. Here are some examples with their prompts, usefulness, and possible outputs:

Prompt 20: Custom eCommerce Functions

"Create a custom function for adding items to a shopping cart in JavaScript."

This prompt is useful when designing eCommerce websites, as it helps you quickly generate a custom function to handle cart operations. An example output:

function addToCart(item, quantity) {
  cart.push({item: item, quantity: quantity});
}

This simple function takes two arguments (item and quantity) and adds a new object to the cart array.

Prompt 21: Design SQL Queries for DB Access

"Design a SQL query to fetch an ordered list of the latest 5 posts with user information."

This prompt is helpful for developers working with databases, as it generates a SQL query for a common task, like displaying recent posts. An example output:

SELECT p.title, p.content, p.created_at, u.username, u.email
FROM posts p
JOIN users u ON p.user_id = u.id
ORDER BY p.created_at DESC
LIMIT 5;

This SQL query fetches the latest 5 posts along with user information, ordered by creation date in descending order.

Prompt 22: Parsing

"Provide a Python code snippet for parsing JSON data and printing specific values."

Great for those interfacing with web APIs, this prompt generates Python code to parse JSON data and access specific values. An example output:

import json

data = '{"name": "John", "city": "New York"}'
parsed_data = json.loads(data)
print(parsed_data['name'], parsed_data['city'])

This code snippet imports the json module, parses a JSON string, and prints the values of the name and city keys.

Industry-Specific Prompts

Let’s explore some ChatGPT prompts specifically designed to cater to industry-specific problem areas.

Prompt 23: Understanding Code Snippet

Help me understand this Python code: [code snippet]

With this prompt, ChatGPT can assist programmers by providing an explanation of the given code snippet, making it easier for them to grasp new concepts or understand existing code. For example, if the code snippet is:

def add(a, b):
    return a + b

The ChatGPT output might be:

This is a simple Python function called 'add' that takes two arguments 'a' and 'b', adds them together, and returns the result. It works with any two numbers.

Prompt 24: Bug Finding II

Find bugs in the following JavaScript code: [code snippet]

This prompt is useful for identifying potential issues or bugs within a provided JavaScript code snippet. For instance, if the code is:

function add(a, b} {
    return a + b;
}

ChatGPT might respond with:

There is a syntax error in the function declaration: the opening curly brace '{' should be replaced with a parenthesis '('. The corrected code should be:

function add(a, b) {
    return a + b;
}

Prompt 25: Optimize SQL Queries

How can I optimize the following SQL query? [SQL query]

This prompt helps developers improve the performance of their SQL queries by suggesting optimization techniques. For example, if the query is:

SELECT * FROM employees WHERE department='IT' OR department='Finance';

ChatGPT might offer:

You can optimize this query by using the IN keyword to condense the WHERE clause. The optimized query would look like this:

SELECT * FROM employees WHERE department IN ('IT', 'Finance');

10 More Helpful Prompts

As a coder, you can leverage ChatGPT to improve your programming skills and get assistance in various coding-related tasks.

Here, we present a list of the 10 most helpful ChatGPT prompts for coders:

  1. Convert the following Python code to JavaScript: {code_snippet} This prompt assists coders in translating Python code into JavaScript. It’s useful when you want to switch languages while maintaining the same functionality. For example, transforming a Python list comprehension to JavaScript’s map function.
  2. Explain the purpose of the following code: {code_snippet} This prompt is helpful when you’re trying to understand someone else’s code or to get an explanation of a new concept. ChatGPT will provide a brief explanation of the code’s purpose and functionality.
  3. Find and fix the bug in this code: {code_snippet} When you’re stuck on a piece of code, this prompt can help you identify and resolve the issue. ChatGPT will analyze the code, pinpoint the bug, and suggest a solution.
  4. What's the best practice for {coding_concept} in {programming_language}? This prompt lets you learn about industry best practices for specific coding concepts and languages. It’s an efficient way to enhance your coding skills and stay updated on the latest practices.
  5. Write a {programming_language} function that takes an array of numbers and returns their sum. This prompt focuses on generating a specific function in a given programming language. You can use it as a starting point for more complex tasks or to practice writing code in a new language.
  6. How do I {programming_task} using the {library_or_framework} in {programming_language}? When working with new libraries or frameworks, use this prompt to get concise guidance on accomplishing a specific programming task. ChatGPT will provide you with examples and explanations to increase your understanding.
  7. Optimize the following code for better performance: {code_snippet} This prompt helps coders identify potential performance improvements in their code. ChatGPT will analyze the code and suggest changes that could result in faster execution times or lower memory consumption.
  8. Compare and contrast {programming_language1} and {programming_language2} in terms of {comparison_point}. Gain insights into different programming languages' relative strengths and weaknesses regarding specific aspects, such as performance, readability, or community support. This information helps make informed decisions when selecting a language for a new project.
  9. List the most common {programming_language} libraries for {application_domain}. Stay updated with libraries that are popular in a particular programming language and application domain. This prompt can help you find the right library for your project and expand your knowledge base.
  10. Write a code review for the following {programming_language} code snippet: {code_snippet} Improve your code review skills by using this prompt, which allows ChatGPT to evaluate a code snippet and provide feedback, suggestions, and potential improvements. Apply these insights to your own code and learn new development techniques.

These prompts provide valuable starting points for engaging with ChatGPT as a coder.

You can further explore resources such as GitHub’s awesome-chatgpt-prompts repository and the FlowGPT website, where you can discover more prompts, communicate with the ChatGPT community, and share your own findings.

Also make sure to check out our prompting cheat sheet for beginners:

πŸ’‘ Recommended: Free ChatGPT Prompting Cheat Sheet

Conclusion

We’ve explored the most helpful ChatGPT prompts specifically tailored for coders. These prompts are designed to assist with tasks like generating code snippets, debugging, offering programming tips, and more.

Remember, the key to getting the most from ChatGPT is to experiment with different prompts and adapt them. Trial and error!

With practice, you can leverage this incredible AI tool to enhance your coding experience and streamline your workflow. Now go forth, explore, and begin reaping the benefits of these powerful prompts for coders! πŸš€

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